Often new products they come with a disclaimer, but in April artificial intelligence company OpenAI issued an unusual warning when it announced a new service called DALL-E 2. The system can generate vivid and realistic photos, images and illustrations in response to a line of text or an uploaded image. One section of OpenAI’s release notes warns that “the model can increase the efficiency of performing some tasks such as photo editing or stock photography production, which could replace the jobs of designers, photographers, models, editors and artists.”
So far this has not happened. People granted early access to DALL-E have found that it enhances human creativity rather than making it obsolete. Benjamin Von Wong, an artist who creates installations and sculptures, says it has actually increased his productivity. “DALL-E is a wonderful tool for someone like me who can’t draw,” says Von Wong, who uses the tool to explore ideas that could later be incorporated into physical artwork. “Instead of having to sketch out concepts, I can simply generate them through different quick phrases.”
DALL-E is one of a number of new AI image generation tools. Aza Raskin, an artist and designer, used open source software to create a music video for musician Zia Cora that was shown at the TED conference in April. The project helped convince him that image-generating artificial intelligence would lead to an explosion of creativity that would permanently change humanity’s visual environment. “Anything that can have a visual, it will have,” he says, potentially disrupting people’s intuition for judging how much time or effort has gone into a project. “Suddenly we have this tool that makes what was hard to imagine and visualize exist.”
It is too early to know how such transformative technology will ultimately affect illustrators, photographers and other creatives. But at this point, the idea that artistic AI tools will displace workers from creative jobs—the way people sometimes describe robots replacing factory workers—seems too simplistic. Even for industrial robots, which perform relatively simple, repetitive tasks, the evidence is mixed. Some economic studies suggest that the adoption of robots by companies results in lower employment and lower wages overall, but there is also evidence that in certain settings robots increase employment opportunities.
“There’s too much doom and gloom in the art community,” where some people too easily assume that machines can replace human creative work, says Noah Bradley, a digital artist who posts YouTube tutorials on using AI tools. Bradley believes the impact of software like DALL-E will be similar to the impact of smartphones on photography – making visual creativity more accessible without replacing professionals. Creating powerful, usable images still requires a lot of fine-tuning after something is first generated, he says. “There’s a lot of complexity in creating art that machines aren’t ready for yet.”
The first version of DALL-E, released in January 2021, was a landmark for computer-generated art. It turned out that fed thousands of images to machine learning algorithms, the training data could reproduce and recombine the features of those existing images in new, coherent, and aesthetically pleasing ways.
A year later, the DALL-E 2 has significantly improved the quality of images that can be produced. It can also reliably adopt different art styles and can produce images that are more photorealistic. Want a studio-quality photo of a Shiba Inu dog wearing a beret and a black turtleneck? Just type it in and wait. A steampunk illustration of a castle in the clouds? No problem. Or a 19th-century-style painting of a group of women signing the Declaration of Independence? Great idea!
Many people experimenting with DALL-E and similar AI tools describe them less as a replacement than as a new kind of artistic assistant or muse. “It’s like talking to an alien entity,” says David R Munson, a photographer, writer and English teacher in Japan who has been using DALL-E for the past two weeks. “It’s trying to understand the text query and tell us what it’s seeing, and it’s just kind of squirming in this amazing way and producing things that you really don’t expect.”